Abstract
It is to be expected that wine production in a certain geographical area may not meet the preferences of consumers worldwide. Consequently, as the global wine market grows, the main challenge is to find the right market to sell a specific product. Being aware of the different sensory preferences of international consumers is fundamental to optimizing commercial strategies and matching supply and demand for global wine traders. Eighteen samples of Chardonnay and Sauvignon Blanc were collected from nine world origins (three origins from New Zealand). The samples were analysed by HS-SPME-GCxGC-TOF/MS and HPLCQqQ/MS, respectively for volatile and phenolic compounds. Moreover, for sensory evaluation, wines were analysed by modified Rate-All-That-Apply. Multivariate statistical methods, such as Multiple Factor Analysis (MFA), Partial Least Square Regression (PLR-R), and Multiple Linear Regression (MLR) were used to assess the quality of the wines, based on sensory and chemical data. As results 1)MFA made it possible to summarize the effects of all analyses in a single statistical model by showing interesting separations between the different wine origins 2)PLS-R showed which sensory variables most influenced the Overall-Quality-Judgment (OQJ), and it was also possible to understand the effect of volatile compounds on aroma sensory variables. 3)MLR showed which volatile compounds influenced the flavour. Consequently, this integrated combination of methods proves to be a powerful tool to provide a deeper and more comprehensive overview of wine quality, which is useful not only for basic research but also as a tool to aid the business-related decision-making activities of wineries and wine traders.